| /** |
| * geostats() is a tiny and standalone javascript library for classification |
| * Project page - https://github.com/simogeo/geostats |
| * Copyright (c) 2011 Simon Georget, http://valums.com |
| * Licensed under the MIT license |
| */ |
| |
| var _t = function(str) { |
| return str; |
| }; |
| |
| var inArray = function(needle, haystack) { |
| for(var i = 0; i < haystack.length; i++) { |
| if(haystack[i] == needle) return true; |
| } |
| return false; |
| }; |
| |
| var geostats = function(a) { |
| |
| this.separator = ' - '; |
| this.legendSeparator = this.separator; |
| this.method = ''; |
| this.roundlength = 2; // Number of decimals, round values |
| this.is_uniqueValues = false; |
| |
| this.bounds = Array(); |
| this.ranges = Array(); |
| this.colors = Array(); |
| this.counter = Array(); |
| |
| // statistics information |
| this.stat_sorted = null; |
| this.stat_mean = null; |
| this.stat_median = null; |
| this.stat_sum = null; |
| this.stat_max = null; |
| this.stat_min = null; |
| this.stat_pop = null; |
| this.stat_variance = null; |
| this.stat_stddev = null; |
| this.stat_cov = null; |
| |
| |
| if(typeof a !== 'undefined' && a.length > 0) { |
| this.serie = a; |
| } else { |
| this.serie = Array(); |
| }; |
| |
| /** |
| * Set a new serie |
| */ |
| this.setSerie = function(a) { |
| |
| this.serie = Array() // init empty array to prevent bug when calling classification after another with less items (sample getQuantile(6) and getQuantile(4)) |
| this.serie = a; |
| |
| }; |
| |
| /** |
| * Set colors |
| */ |
| this.setColors = function(colors) { |
| |
| this.colors = colors; |
| |
| }; |
| |
| /** |
| * Get feature count |
| * With bounds array(0, 0.75, 1.5, 2.25, 3); |
| * should populate this.counter with 5 keys |
| * and increment counters for each key |
| */ |
| this.doCount = function() { |
| |
| if (this._nodata()) |
| return; |
| |
| |
| var tmp = this.sorted(); |
| // console.log(tmp.join(', ')); |
| |
| |
| // we init counter with 0 value |
| for(i = 0; i < this.bounds.length; i++) { |
| this.counter[i]= 0; |
| } |
| |
| for(j=0; j < tmp.length; j++) { |
| |
| // get current class for value to increment the counter |
| var cclass = this.getClass(tmp[j]); |
| this.counter[cclass]++; |
| |
| } |
| |
| }; |
| |
| /** |
| * Transform a bounds array to a range array the following array : array(0, |
| * 0.75, 1.5, 2.25, 3); becomes : array('0-0.75', '0.75-1.5', '1.5-2.25', |
| * '2.25-3'); |
| */ |
| this.setRanges = function() { |
| |
| this.ranges = Array(); // init empty array to prevent bug when calling classification after another with less items (sample getQuantile(6) and getQuantile(4)) |
| |
| for (i = 0; i < (this.bounds.length - 1); i++) { |
| this.ranges[i] = this.bounds[i] + this.separator + this.bounds[i + 1]; |
| } |
| }; |
| |
| /** return min value */ |
| this.min = function() { |
| |
| if (this._nodata()) |
| return; |
| |
| if (this.stat_min == null) { |
| |
| this.stat_min = this.serie[0]; |
| for (i = 0; i < this.pop(); i++) { |
| if (this.serie[i] < this.stat_min) { |
| this.stat_min = this.serie[i]; |
| } |
| } |
| |
| } |
| |
| return this.stat_min; |
| }; |
| |
| /** return max value */ |
| this.max = function() { |
| |
| if (this._nodata()) |
| return; |
| |
| if (this.stat_max == null) { |
| |
| this.stat_max = this.serie[0]; |
| for (i = 0; i < this.pop(); i++) { |
| if (this.serie[i] > this.stat_max) { |
| this.stat_max = this.serie[i]; |
| } |
| } |
| |
| } |
| |
| return this.stat_max; |
| }; |
| |
| /** return sum value */ |
| this.sum = function() { |
| |
| if (this._nodata()) |
| return; |
| |
| if (this.stat_sum == null) { |
| |
| this.stat_sum = 0; |
| for (i = 0; i < this.pop(); i++) { |
| this.stat_sum += this.serie[i]; |
| } |
| |
| } |
| |
| return this.stat_sum; |
| }; |
| |
| /** return population number */ |
| this.pop = function() { |
| |
| if (this._nodata()) |
| return; |
| |
| if (this.stat_pop == null) { |
| |
| this.stat_pop = this.serie.length; |
| |
| } |
| |
| return this.stat_pop; |
| }; |
| |
| /** return mean value */ |
| this.mean = function() { |
| |
| if (this._nodata()) |
| return; |
| |
| if (this.stat_mean == null) { |
| |
| this.stat_mean = this.sum() / this.pop(); |
| |
| } |
| |
| return this.stat_mean; |
| }; |
| |
| /** return median value */ |
| this.median = function() { |
| |
| if (this._nodata()) |
| return; |
| |
| if (this.stat_median == null) { |
| |
| this.stat_median = 0; |
| var tmp = this.sorted(); |
| |
| if (tmp.length % 2) { |
| this.stat_median = tmp[(Math.ceil(tmp.length / 2) - 1)]; |
| } else { |
| this.stat_median = (tmp[(tmp.length / 2) - 1] + tmp[(tmp.length / 2)]) / 2; |
| } |
| |
| } |
| |
| return this.stat_median; |
| }; |
| |
| /** return variance value */ |
| this.variance = function() { |
| |
| round = (typeof round === "undefined") ? true : false; |
| |
| if (this._nodata()) |
| return; |
| |
| if (this.stat_variance == null) { |
| |
| var tmp = 0; |
| for (var i = 0; i < this.pop(); i++) { |
| tmp += Math.pow( (this.serie[i] - this.mean()), 2 ); |
| } |
| |
| this.stat_variance = tmp / this.pop(); |
| |
| if(round == true) { |
| this.stat_variance = Math.round(this.stat_variance * Math.pow(10,this.roundlength) )/ Math.pow(10,this.roundlength); |
| } |
| |
| } |
| |
| return this.stat_variance; |
| }; |
| |
| /** return standard deviation value */ |
| this.stddev = function(round) { |
| |
| round = (typeof round === "undefined") ? true : false; |
| |
| if (this._nodata()) |
| return; |
| |
| if (this.stat_stddev == null) { |
| |
| this.stat_stddev = Math.sqrt(this.variance()); |
| |
| if(round == true) { |
| this.stat_stddev = Math.round(this.stat_stddev * Math.pow(10,this.roundlength) )/ Math.pow(10,this.roundlength); |
| } |
| |
| } |
| |
| return this.stat_stddev; |
| }; |
| |
| /** coefficient of variation - measure of dispersion */ |
| this.cov = function(round) { |
| |
| round = (typeof round === "undefined") ? true : false; |
| |
| if (this._nodata()) |
| return; |
| |
| if (this.stat_cov == null) { |
| |
| this.stat_cov = this.stddev() / this.mean(); |
| |
| if(round == true) { |
| this.stat_cov = Math.round(this.stat_cov * Math.pow(10,this.roundlength) )/ Math.pow(10,this.roundlength); |
| } |
| |
| } |
| |
| return this.stat_cov; |
| }; |
| |
| /** data test */ |
| this._nodata = function() { |
| if (this.serie.length == 0) { |
| |
| alert("Error. You should first enter a serie!"); |
| return 1; |
| } else |
| return 0; |
| |
| }; |
| |
| /** return sorted values (as array) */ |
| this.sorted = function() { |
| |
| if (this.stat_sorted == null) { |
| |
| if(this.is_uniqueValues == false) { |
| this.stat_sorted = this.serie.sort(function(a, b) { |
| return a - b; |
| }); |
| } else { |
| this.stat_sorted = this.serie.sort(function(a,b){ |
| var nameA=a.toLowerCase(), nameB=b.toLowerCase() |
| if(nameA < nameB) return -1; |
| if(nameA > nameB) return 1; |
| return 0; |
| }) |
| } |
| } |
| |
| return this.stat_sorted; |
| |
| }; |
| |
| /** return all info */ |
| this.info = function() { |
| |
| if (this._nodata()) |
| return; |
| |
| var content = ''; |
| content += _t('Population') + ' : ' + this.pop() + ' - [' + _t('Min') |
| + ' : ' + this.min() + ' | ' + _t('Max') + ' : ' + this.max() |
| + ']' + "\n"; |
| content += _t('Mean') + ' : ' + this.mean() + ' - ' + _t('Median') + ' : ' + this.median() + "\n"; |
| content += _t('Variance') + ' : ' + this.variance() + ' - ' + _t('Standard deviation') + ' : ' + this.stddev() |
| + ' - ' + _t('Coefficient of variation') + ' : ' + this.cov() + "\n"; |
| |
| return content; |
| }; |
| |
| /** |
| * Equal intervals discretization Return an array with bounds : ie array(0, |
| * 0.75, 1.5, 2.25, 3); |
| */ |
| this.getEqInterval = function(nbClass) { |
| |
| if (this._nodata()) |
| return; |
| |
| this.method = _t('eq. intervals') + ' (' + nbClass + ' ' + _t('classes') |
| + ')'; |
| |
| var a = Array(); |
| var val = this.min(); |
| var interval = (this.max() - this.min()) / nbClass; |
| |
| for (i = 0; i <= nbClass; i++) { |
| a[i] = val; |
| val += interval; |
| } |
| |
| this.bounds = a; |
| this.setRanges(); |
| |
| return a; |
| }; |
| |
| |
| /** |
| * Quantile discretization Return an array with bounds : ie array(0, 0.75, |
| * 1.5, 2.25, 3); |
| */ |
| this.getQuantile = function(nbClass) { |
| |
| if (this._nodata()) |
| return; |
| |
| this.method = _t('quantile') + ' (' + nbClass + ' ' + _t('classes') + ')'; |
| |
| var a = Array(); |
| var tmp = this.sorted(); |
| |
| var classSize = Math.round(this.pop() / nbClass); |
| var step = classSize; |
| var i = 0; |
| |
| // we set first value |
| a[0] = tmp[0]; |
| |
| for (i = 1; i < nbClass; i++) { |
| a[i] = tmp[step]; |
| step += classSize; |
| } |
| // we set last value |
| a.push(tmp[tmp.length - 1]); |
| |
| this.bounds = a; |
| this.setRanges(); |
| |
| return a; |
| |
| }; |
| |
| /** |
| * Credits : Doug Curl (javascript) and Daniel J Lewis (python implementation) |
| * http://www.arcgis.com/home/item.html?id=0b633ff2f40d412995b8be377211c47b |
| * http://danieljlewis.org/2010/06/07/jenks-natural-breaks-algorithm-in-python/ |
| */ |
| this.getJenks = function(nbClass) { |
| |
| if (this._nodata()) |
| return; |
| |
| this.method = _t('Jenks') + ' (' + nbClass + ' ' + _t('classes') + ')'; |
| |
| dataList = this.sorted(); |
| |
| // now iterate through the datalist: |
| // determine mat1 and mat2 |
| // really not sure how these 2 different arrays are set - the code for |
| // each seems the same! |
| // but the effect are 2 different arrays: mat1 and mat2 |
| var mat1 = [] |
| for ( var x = 0, xl = dataList.length + 1; x < xl; x++) { |
| var temp = [] |
| for ( var j = 0, jl = nbClass + 1; j < jl; j++) { |
| temp.push(0) |
| } |
| mat1.push(temp) |
| } |
| |
| var mat2 = [] |
| for ( var i = 0, il = dataList.length + 1; i < il; i++) { |
| var temp2 = [] |
| for ( var c = 0, cl = nbClass + 1; c < cl; c++) { |
| temp2.push(0) |
| } |
| mat2.push(temp2) |
| } |
| |
| // absolutely no idea what this does - best I can tell, it sets the 1st |
| // group in the |
| // mat1 and mat2 arrays to 1 and 0 respectively |
| for ( var y = 1, yl = nbClass + 1; y < yl; y++) { |
| mat1[0][y] = 1 |
| mat2[0][y] = 0 |
| for ( var t = 1, tl = dataList.length + 1; t < tl; t++) { |
| mat2[t][y] = Infinity |
| } |
| var v = 0.0 |
| } |
| |
| // and this part - I'm a little clueless on - but it works |
| // pretty sure it iterates across the entire dataset and compares each |
| // value to |
| // one another to and adjust the indices until you meet the rules: |
| // minimum deviation |
| // within a class and maximum separation between classes |
| for ( var l = 2, ll = dataList.length + 1; l < ll; l++) { |
| var s1 = 0.0 |
| var s2 = 0.0 |
| var w = 0.0 |
| for ( var m = 1, ml = l + 1; m < ml; m++) { |
| var i3 = l - m + 1 |
| var val = parseFloat(dataList[i3 - 1]) |
| s2 += val * val |
| s1 += val |
| w += 1 |
| v = s2 - (s1 * s1) / w |
| var i4 = i3 - 1 |
| if (i4 != 0) { |
| for ( var p = 2, pl = nbClass + 1; p < pl; p++) { |
| if (mat2[l][p] >= (v + mat2[i4][p - 1])) { |
| mat1[l][p] = i3 |
| mat2[l][p] = v + mat2[i4][p - 1] |
| } |
| } |
| } |
| } |
| mat1[l][1] = 1 |
| mat2[l][1] = v |
| } |
| |
| var k = dataList.length |
| var kclass = [] |
| |
| // fill the kclass (classification) array with zeros: |
| for (i = 0, il = nbClass + 1; i < il; i++) { |
| kclass.push(0) |
| } |
| |
| // this is the last number in the array: |
| kclass[nbClass] = parseFloat(dataList[dataList.length - 1]) |
| // this is the first number - can set to zero, but want to set to lowest |
| // to use for legend: |
| kclass[0] = parseFloat(dataList[0]) |
| var countNum = nbClass |
| while (countNum >= 2) { |
| var id = parseInt((mat1[k][countNum]) - 2) |
| kclass[countNum - 1] = dataList[id] |
| k = parseInt((mat1[k][countNum] - 1)) |
| // spits out the rank and value of the break values: |
| // console.log("id="+id,"rank = " + String(mat1[k][countNum]),"val = |
| // " + String(dataList[id])) |
| // count down: |
| countNum -= 1 |
| } |
| // check to see if the 0 and 1 in the array are the same - if so, set 0 |
| // to 0: |
| if (kclass[0] == kclass[1]) { |
| kclass[0] = 0 |
| } |
| |
| this.bounds = kclass; |
| this.setRanges(); |
| |
| return kclass; //array of breaks |
| } |
| |
| |
| /** |
| * Quantile discretization Return an array with bounds : ie array(0, 0.75, |
| * 1.5, 2.25, 3); |
| */ |
| this.getUniqueValues = function() { |
| |
| if (this._nodata()) |
| return; |
| |
| this.method = _t('unique values'); |
| this.is_uniqueValues = true; |
| |
| var tmp = this.sorted(); // display in alphabetical order |
| |
| var a = Array(); |
| |
| for (i = 0; i < this.pop(); i++) { |
| if(!inArray (tmp[i], a)) |
| a.push(tmp[i]); |
| } |
| |
| this.bounds = a; |
| |
| return a; |
| |
| }; |
| |
| |
| /** |
| * Return the class of a given value. |
| * For example value : 6 |
| * and bounds array = (0, 4, 8, 12); |
| * Return 2 |
| */ |
| this.getClass = function(value) { |
| |
| for(i = 0; i < this.bounds.length; i++) { |
| |
| |
| if(this.is_uniqueValues == true) { |
| if(value == this.bounds[i]) |
| return i; |
| } else { |
| if(value <= this.bounds[i + 1]) { |
| return i; |
| } |
| } |
| } |
| |
| return _t("Unable to get value's class."); |
| |
| }; |
| |
| /** |
| * Return the ranges array : array('0-0.75', '0.75-1.5', '1.5-2.25', |
| * '2.25-3'); |
| */ |
| this.getRanges = function() { |
| |
| return this.ranges; |
| |
| }; |
| |
| /** |
| * Returns the number/index of this.ranges that value falls into |
| */ |
| this.getRangeNum = function(value) { |
| var bounds, i; |
| |
| for (i = 0; i < this.ranges.length; i++) { |
| bounds = this.ranges[i].split(/ - /); |
| if (value <= parseFloat(bounds[1])) { |
| return i; |
| } |
| } |
| } |
| |
| /** |
| * Return an html legend |
| * |
| */ |
| this.getHtmlLegend = function(colors, legend, counter, callback) { |
| |
| var cnt= ''; |
| |
| if(colors != null) { |
| ccolors = colors; |
| } |
| else { |
| ccolors = this.colors; |
| } |
| |
| if(legend != null) { |
| lg = legend; |
| } |
| else { |
| lg = 'Legend'; |
| } |
| |
| if(counter != null) { |
| this.doCount(); |
| getcounter = true; |
| } |
| else { |
| getcounter = false; |
| } |
| |
| if(callback != null) { |
| fn = callback; |
| } |
| else { |
| fn = function(o) {return o;}; |
| } |
| |
| |
| if(ccolors.length < this.ranges.length) { |
| alert(_t('The number of colors should fit the number of ranges. Exit!')); |
| return; |
| } |
| |
| var content = '<div class="geostats-legend"><div class="geostats-legend-title">' + _t(lg) + '</div>'; |
| |
| if(this.is_uniqueValues == false) { |
| for (i = 0; i < (this.ranges.length); i++) { |
| if(getcounter===true) { |
| cnt = ' <span class="geostats-legend-counter">(' + this.counter[i] + ')</span>'; |
| } |
| |
| // check if it has separator or not |
| if(this.ranges[i].indexOf(this.separator) != -1) { |
| var tmp = this.ranges[i].split(this.separator); |
| var el = fn(tmp[0]) + this.legendSeparator + fn(tmp[1]); |
| } else { |
| var el = fn(this.ranges[i]); |
| } |
| content += '<div><div class="geostats-legend-block" style="background-color:' + ccolors[i] + '"></div> ' + el + cnt + '</div>'; |
| } |
| } else { |
| // only if classification is done on unique values |
| for (i = 0; i < (this.bounds.length); i++) { |
| if(getcounter===true) { |
| cnt = ' <span class="geostats-legend-counter">(' + this.counter[i] + ')</span>'; |
| } |
| var el = fn(this.bounds[i]); |
| content += '<div><div class="geostats-legend-block" style="background-color:' + ccolors[i] + '"></div> ' + el + cnt + '</div>'; |
| } |
| } |
| content += '</div>'; |
| return content; |
| }; |
| |
| this.getSortedlist = function() { |
| return this.sorted().join(', '); |
| }; |
| |
| }; |